This viewer was created for the Arkansas GIS Office to aid staff as well as County personnel in quickly locating information related to tax parcels.

Vector polygon map data of property parcels from St. Francis County, Arkansas containing 18,202 features.

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Property parcel GIS map data consists of detailed information about individual land parcels, including their boundaries, ownership details, and geographic coordinates.

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Property parcel data can be used to analyze and visualize land-related information for purposes such as real estate assessment, urban planning, or environmental management.

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Available for viewing and sharing as a map in a Koordinates map viewer. This data is also available for export to DWG for CAD, PDF, KML, CSV, and GIS data formats, including Shapefile, MapInfo, and Geodatabase.

The TIGER/Line shapefiles and related database files (.dbf) are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). The MTDB represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line shapefile is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. County subdivisions are the primary divisions of counties and their equivalent entities for the reporting of Census Bureau data. They include legally-recognized minor civil divisions (MCDs) and statistical census county divisions (CCDs), and unorganized territories. For the 2010 Census, the MCDs are the primary governmental and/or administrative divisions of counties in 29 States and Puerto Rico; Tennessee changed from having CCDs for Census 2000 to having MCDs for the 2010 Census. In MCD States where no MCD exists or is not defined, the Census Bureau creates statistical unorganized territories to complete coverage. The entire area of the United States, Puerto Rico, and the Island Areas are covered by county subdivisions. The boundaries of most legal MCDs are as of January 1, 2015, as reported through the Census Bureau's Boundary and Annexation Survey (BAS). The boundaries of all CCDs, delineated in 20 states, are those as reported as part of the Census Bureau's Participant Statistical Areas Program (PSAP) for the 2010 Census.

The 2022 cartographic boundary KMLs are simplified representations of selected geographic areas from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). These boundary files are specifically designed for small-scale thematic mapping. When possible, generalization is performed with the intent to maintain the hierarchical relationships among geographies and to maintain the alignment of geographies within a file set for a given year. Geographic areas may not align with the same areas from another year. Some geographies are available as nation-based files while others are available only as state-based files. The cartographic boundary files include both incorporated places (legal entities) and census designated places or CDPs (statistical entities). An incorporated place is established to provide governmental functions for a concentration of people as opposed to a minor civil division (MCD), which generally is created to provide services or administer an area without regard, necessarily, to population. Places always nest within a state, but may extend across county and county subdivision boundaries. An incorporated place usually is a city, town, village, or borough, but can have other legal descriptions. CDPs are delineated for the decennial census as the statistical counterparts of incorporated places. CDPs are delineated to provide data for settled concentrations of population that are identifiable by name, but are not legally incorporated under the laws of the state in which they are located. The boundaries for CDPs often are defined in partnership with state, local, and/or tribal officials and usually coincide with visible features or the boundary of an adjacent incorporated place or another legal entity. CDP boundaries often change from one decennial census to the next with changes in the settlement pattern and development; a CDP with the same name as in an earlier census does not necessarily have the same boundary. The only population/housing size requirement for CDPs is that they must contain some housing and population. The generalized boundaries of most incorporated places in this file are based on those as of January 1, 2022, as reported through the Census Bureau's Boundary and Annexation Survey (BAS). The generalized boundaries of all CDPs are based on those delineated as part of the Census Bureau's Participant Statistical Areas Program (PSAP) for the 2020 Census.

Geospatial data is comprised of government boundaries.

description: The Arkansas Secretary of State contracted the University of Arkansas at Little Rock, GIS Applications Laboratory (UALRGIS) to use modern geographic information technology and improved base maps to create a current and spatially accurate statewide depiction of school district boundaries in the State of Arkansas. The Arkansas Geographic Information Office merged annexed and consolidated districts. UALRGIS followed a work plan for the project that was established by the Arkansas Geographic Information Office (AGIO) for the Secretary of State. The school district boundary editing rules were as follows: 1. Legal descriptions take precedent. 2. If no legal description was provided the visual evidence presented on the digital ortho quarter quadrangle (DOQQ) was followed. 3. Section lines, county boundaries, city boundaries and / or roads have only be used as supporting visual evidence viewed on the DOQQ.; abstract: The Arkansas Secretary of State contracted the University of Arkansas at Little Rock, GIS Applications Laboratory (UALRGIS) to use modern geographic information technology and improved base maps to create a current and spatially accurate statewide depiction of school district boundaries in the State of Arkansas. The Arkansas Geographic Information Office merged annexed and consolidated districts. UALRGIS followed a work plan for the project that was established by the Arkansas Geographic Information Office (AGIO) for the Secretary of State. The school district boundary editing rules were as follows: 1. Legal descriptions take precedent. 2. If no legal description was provided the visual evidence presented on the digital ortho quarter quadrangle (DOQQ) was followed. 3. Section lines, county boundaries, city boundaries and / or roads have only be used as supporting visual evidence viewed on the DOQQ.

The USGS Protected Areas Database of the United States (PAD-US) is the nation's inventory of protected areas, including public open space and voluntarily provided, private protected areas, identified as an A-16 National Geospatial Data Asset in the Cadastral Theme (http://www.fgdc.gov/ngda-reports/NGDA_Datasets.html). PAD-US is an ongoing project with several published versions of a spatial database of areas dedicated to the preservation of biological diversity, and other natural, recreational or cultural uses, managed for these purposes through legal or other effective means. The geodatabase maps and describes public open space and other protected areas. Most areas are public lands owned in fee; however, long-term easements, leases, and agreements or administrative designations documented in agency management plans may be included. The PAD-US database strives to be a complete “best available” inventory of protected areas (lands and waters) including data provided by managing agencies and organizations. The dataset is built in collaboration with several partners and data providers (http://gapanalysis.usgs.gov/padus/stewards/). See Supplemental Information Section of this metadata record for more information on partnerships and links to major partner organizations. As this dataset is a compilation of many data sets; data completeness, accuracy, and scale may vary. Federal and state data are generally complete, while local government and private protected area coverage is about 50% complete, and depends on data management capacity in the state. For completeness estimates by state: http://www.protectedlands.net/partners. As the federal and state data are reasonably complete; focus is shifting to completing the inventory of local gov and voluntarily provided, private protected areas. The PAD-US geodatabase contains over twenty-five attributes and four feature classes to support data management, queries, web mapping services and analyses: Marine Protected Areas (MPA), Fee, Easements and Combined. The data contained in the MPA Feature class are provided directly by the National Oceanic and Atmospheric Administration (NOAA) Marine Protected Areas Center (MPA, http://marineprotectedareas.noaa.gov ) tracking the National Marine Protected Areas System. The Easements feature class contains data provided directly from the National Conservation Easement Database (NCED, http://conservationeasement.us ) The MPA and Easement feature classes contain some attributes unique to the sole source databases tracking them (e.g. Easement Holder Name from NCED, Protection Level from NOAA MPA Inventory). The "Combined" feature class integrates all fee, easement and MPA features as the best available national inventory of protected areas in the standard PAD-US framework. In addition to geographic boundaries, PAD-US describes the protection mechanism category (e.g. fee, easement, designation, other), owner and managing agency, designation type, unit name, area, public access and state name in a suite of standardized fields. An informative set of references (i.e. Aggregator Source, GIS Source, GIS Source Date) and "local" or source data fields provide a transparent link between standardized PAD-US fields and information from authoritative data sources. The areas in PAD-US are also assigned conservation measures that assess management intent to permanently protect biological diversity: the nationally relevant "GAP Status Code" and global "IUCN Category" standard. A wealth of attributes facilitates a wide variety of data analyses and creates a context for data to be used at local, regional, state, national and international scales. More information about specific updates and changes to this PAD-US version can be found in the Data Quality Information section of this metadata record as well as on the PAD-US website, http://gapanalysis.usgs.gov/padus/data/history/.) Due to the completeness and complexity of these data, it is highly recommended to review the Supplemental Information Section of the metadata record as well as the Data Use Constraints, to better understand data partnerships as well as see tips and ideas of appropriate uses of the data and how to parse out the data that you are looking for. For more information regarding the PAD-US dataset please visit, http://gapanalysis.usgs.gov/padus/. To find more data resources as well as view example analysis performed using PAD-US data visit, http://gapanalysis.usgs.gov/padus/resources/. The PAD-US dataset and data standard are compiled and maintained by the USGS Gap Analysis Program, http://gapanalysis.usgs.gov/ . For more information about data standards and how the data are aggregated please review the “Standards and Methods Manual for PAD-US,” http://gapanalysis.usgs.gov/padus/data/standards/ .

Map showing the statistical neighborhoods of Wyandotte County.By using this dataset you acknowledge the following:Kansas Open Records Act StatementThe Kansas Open Records Act provides in K.S.A. 45-230 that "no person shall knowingly sell, give or receive, for the purpose of selling or offering for sale, any property or service to persons listed therein, any list of names and addresses contained in, or derived from public records..." Violation of this law may subject the violator to a civil penalty of $500.00 for each violation. Violators will be reported for prosecution.By accessing this site, the user makes the following certification pursuant to K.S.A. 45-220(c)(2): "The requester does not intend to, and will not: (A) Use any list of names or addresses contained in or derived from the records or information for the purpose of selling or offering for sale any property or service to any person listed or to any person who resides at any address listed; or (B) sell, give or otherwise make available to any person any list of names or addresses contained in or derived from the records or information for the purpose of allowing that person to sell or offer for sale any property or service to any person listed or to any person who resides at any address listed."

According to Cognitive Market Research, the global 3D Mapping and Modeling market size is USD 5218.3 million in 2024 and will expand at a compound yearly growth rate (CAGR) of 16.3% from 2024 to 2031. Market Dynamics of 3D Mapping and Modeling Market

Key Drivers for 3D Mapping and Modeling Market

Enhanced Customer Experience to Increase Demand Globally of the 3D Mappinf and Modelling Market

Enhanced customer experience drives the 3D mapping and modeling market by offering immersive and interactive experiences. In sectors like tourism, customers can explore destinations virtually before visiting, increasing engagement and satisfaction. In retail, 3D modeling enables personalized product visualization, aiding in purchasing decisions. Additionally, in architecture and real estate, clients can virtually tour properties, facilitating better-informed choices. Scalability and Flexibility- The Flexibility and scalability of 3D mapping and modeling solutions enable them to adapt to various industries and applications, driving market growth by catering to diverse needs and evolving technological requirements.

Key Restraints for 3D Mapping and Modeling Market

Cost of Technology is a key restraint for the growth of the 3D Mapping and Modelling Market. 

The high cost of 3D mapping and modeling technologies often acts as a barrier to entry for smaller businesses and limits widespread adoption across industries. Complexity and Skill Need- The complexity and high skill requirements involved in 3D mapping and modeling processes can limit market growth by creating barriers to entry for smaller businesses and increasing costs for training and implementation.

Opportunity for the growth of 3D Mapping and Modeling Market

The Augmented reality (AR) and virtual reality (VR) across various sectors present a key opportunity for the growth of 3D Mapping and Modeling Market

One major opportunity for the growth of the 3D mapping and modeling market lies in the rapid adoption of augmented reality (AR) and virtual reality (VR) across sectors such as gaming, urban planning, real estate, automotive, and healthcare. As industries increasingly embrace immersive technologies to enhance user engagement, design accuracy, and operational efficiency, the demand for precise, high-resolution 3D maps and models is surging. AR and VR applications require spatially accurate, real-world overlays and simulations, which depend heavily on 3D data to create seamless, interactive experiences. For instance, city planners are using 3D models for infrastructure development and simulation of traffic flows, while real estate professionals leverage virtual walkthroughs using 3D layouts of properties. Meanwhile, in healthcare, 3D modeling assists in pre-surgical planning and educational simulations. This growing reliance on immersive and spatial technologies is creating strong incentives for companies to invest in advanced 3D mapping and modeling tools, thus accelerating market growth. . Introduction of the 3D Mapping and Modeling Market

The 3D mapping and modeling market encompasses technologies that enable the creation of three-dimensional representations of physical objects, environments, or surfaces. Utilizing techniques such as laser scanning, photogrammetry, LiDAR, and structured light, this market caters to a wide range of industries, including construction, architecture, urban planning, entertainment, and geospatial mapping. These technologies capture detailed spatial data, which is then processed to generate accurate and realistic 3D models. Applications range from creating digital twins of buildings and infrastructure for architectural design and urban planning to virtual tourism experiences and immersive gaming environments. The demand for 3D mapping and modeling solutions is driven by the need for accurate spatial data analysis, visualization, and simulation across diverse sectors, promising enhanced efficiency, cost-effectiveness, and innovative experiences.